Our prime objective is to predict fetal malnutrition from a single set of maternal measurements obtained at midpregnancy. We hypothesize that maternal nutrition is a major regulator of rapidly replicating cells in the maternal environment. Fetal and placental cells are rapidly replicating and growing cells; so are maternal leukocytes. Thus we propose that maternal nutrition will regulate metabolism of leukocytes. Therefore, maternal leukocyte metabolism, taken with objective indicators of nutrient status, might be used to predict fetal growth. Fetal growth is evaluated at birth, by comparison of the expected size of the baby with its actual observed size. Expected size is estimated by taking into account confounding variables, e.g., gestational age, sex, race, mother's size, etc. We presently define a fetally malnourished (FM) baby as one whose observed size deviates more than 1 SD below the expected size for that baby. Expected size is computed by adjusting for 8 variables. The multiple regression equations have been constructed from 200 mother-baby pairs in our sample. We predict the deviations from adjusted birth size (wt., length and head circumference) using maternal variables measured once after 20 weeks of gestation. Currently we are measuring plasma nutrient levels and metabolites, hair root protein and DNA, and socio-cultural characteristics. The measurements are subjected to multivariate analyses. Preliminary variables selected by stepwise multiple regression correlate (R) significantly (p less than 0.05) with adjusted birth measures of the baby. Thus we will be able to predict fetal growth from our midpregnancy measures. The current phase of the project is expanding the data base, testing and refining the prediction equations.